EM Method

In unsupervised learning, what is lost is the label of each data compared with supervised learning. Which is considered as the missing parameters. This is equal to the problem which EM algorithm trying to solve.

So we first estimate the probability of Labels -> E-Step

Then using this Labels, to compute the ML of parameters -> M-Step

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